Business AI Explained

Vlad

Business AI Explained is a podcast for founders and go-to-market teams who want to understand how AI creates real business impact. Hosted by Vlad de Ziegler, the show features conversations with builders, operators, and revenue leaders implementing AI in sales, marketing, RevOps, and customer success. Expect real examples, real constraints, and clear lessons from AI in production, not theory.

Épisodes

  1. From Bankruptcy to Building Booxkeeping: Max Emma on Franchising, Bookkeeping and AI in Operations

    -1 J

    From Bankruptcy to Building Booxkeeping: Max Emma on Franchising, Bookkeeping and AI in Operations

    Max Emma started in landscaping and construction, then got hit hard during the 2008 recession, a period that eventually led to bankruptcy and some hard-earned lessons about risk, financial management, and resilience. He later co-founded Booxkeeping, a bookkeeping business built around fixed pricing, operational efficiency, and standardized financial reporting. That business went on to scale through franchising, becoming a standout model in the bookkeeping industry. In this episode of Business AI Explained, Vlad sits down with Max to unpack that journey and explore how AI is being used inside real business operations today. They discuss where AI genuinely saves time, why custom AI builds often disappoint, and how off-the-shelf tools like ChatGPT and QuickBooks can create real leverage when applied to the right workflows. They cover:  Lessons from the construction industry and the 2008 recession  The path from bankruptcy to building a new business  Why bookkeeping was the opportunity Max chose to pursue  How Booxkeeping scaled through franchising  Where AI works well in finance and ops  Why custom AI tools can be costly and impractical  How AI helps evaluate franchise territories faster  Using AI to automate notes, emails, and internal workflows  Why efficiency gains matter more than hype  How lower operating costs can become a competitive advantage This episode is for founders, operators, franchise builders, finance leaders, and anyone trying to understand what practical AI adoption looks like inside a real business. Where to find Max Emma:  → LinkedIn: https://www.linkedin.com/in/maxemma/ → Company: https://www.linkedin.com/company/booxkeeping/ Work with Vlad:  If you’re implementing AI in your operations and want hands-on help building real workflows:  → https://www.elementsagents.com/ Subscribe / follow Vlad: → LinkedIn: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad

    35 min
  2. AI Adoption Playbook for Sales, CS and Marketing | Charlotte Lucas, ScorePlay

    31 MARS

    AI Adoption Playbook for Sales, CS and Marketing | Charlotte Lucas, ScorePlay

    AI adoption usually breaks when companies try to force it top-down or keep it stuck in experimentation. Charlotte Lucas is Head of Strategy at ScorePlay, where she’s driving AI adoption across the business to help teams in sales, customer success, marketing, and operations move faster and work smarter. As ScorePlay competes in sports broadcasting with a lean team, Charlotte is building practical AI workflows that save time, improve execution, and help teams scale without losing the human touch.  In this episode of Business AI Explained, we break down what AI adoption actually looks like when it works: how to get buy-in, where to start, which workflows to prioritize, and how to combine executive sponsorship with team-level ownership. We also cover how AI can support relationship-driven work, why shared learning matters, and how to build trust in AI outputs across the company.  We cover:  Why AI adoption works best when leadership sponsors it, but teams own the use cases  How to start with small, practical workflows that build trust quickly  How ScorePlay is using AI across lead generation, deal desk ops, customer success, and marketing  Why peer learning, internal sessions, and shared channels accelerate adoption  How to match the right AI tools to the right teams  What strong governance looks like: access, review loops, and exception handling  How AI can strengthen relationship-driven work instead of replacing it  Why automating high-impact, low-complexity workflows creates leverage across the business  How unstructured data can become a strategic advantage with the right AI workflows  What it takes to build an AI culture that works both top-down and bottom-up This conversation is for founders, operators, GTM leaders, strategy teams, and department heads trying to move from AI experimentation to real adoption across the company. Episode length: ~45 minutes 👤 ABOUT THE GUEST Charlotte Lucas Head of Strategy, ScorePlay Charlotte Lucas leads strategy at ScorePlay and is driving AI adoption across the company to help teams save time, improve execution, and support sales, customer success, and marketing at scale. → LinkedIn: https://www.linkedin.com/in/charlotte-lucas-ba479125/ → Company: https://www.scoreplay.io/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    37 min
  3. AI in Sales: How Enterprises Use Chatbots, Data & Automation to Close More Deals

    24 MARS

    AI in Sales: How Enterprises Use Chatbots, Data & Automation to Close More Deals

    AI is no longer just a buzzword in sales, it’s becoming the backbone of how companies engage customers, qualify leads, and scale go-to-market. In this episode, I’m joined by Adis Ceman, Regional Enterprise Sales Director at Cequens, a company building AI-powered communication systems across channels like WhatsApp, SMS, and voice. We go deep into how enterprises are actually using AI today, beyond the hype. We cover:  How AI chatbots are replacing missed opportunities in customer support  Why most companies fail at AI How to structure your data and prompts to get real results  How AI is used in enterprise sales (lead generation, qualification, demos)  The role of human touch in high-value deals (and why it still matters)  How to use AI internally to train teams, build proposals, and move faster  What signals actually matter when selling to enterprise clients  Why speed + personalization are the real competitive advantages in 2026 One of the most valuable insights: AI doesn’t replace sales teams, it makes them faster, sharper, and more responsive. If you're building a product, running sales, or thinking about implementing AI in your company, this episode will give you a clear, practical view of what works. Episode length: ~24 minutes 👤 ABOUT THE GUEST Adis Ceman Regional Sales Director at Cequens - UAE → LinkedIn: https://www.linkedin.com/in/adisceman/ → Company: https://www.cequens.com/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    24 min
  4. How AI Is Rewriting Hiring and Operations | Sean Griffith (Founder of Truffle)

    17 MARS

    How AI Is Rewriting Hiring and Operations | Sean Griffith (Founder of Truffle)

    Many companies are experimenting with AI. But very few are restructuring their operations around it. In this episode of Business AI Explained, Vladimir de Ziegler sits down with Sean Griffith, founder of Truffle, to discuss how AI is reshaping hiring, software workflows, and internal operations. Sean explains how his team is able to produce the same level of output with fewer than 10 people compared to what he previously experienced inside a publicly listed company doing over $300M in ARR. The conversation explores how startups and modern teams are beginning to replace traditional software tools with AI-driven workflows and how leaders can rethink operations to become fully AI-native. Sean also explains how Truffle is redesigning the hiring process using AI-assisted candidate screening, transcription, and evaluation to help HR teams move from hundreds of applicants to a shortlist much faster. The conversation covers: • How startups can control costs when rolling out AI features • Quick SEO opportunities to appear in LLM search results • How developers are replacing traditional software with Claude Code • How to structure operations for AI-native teams • Which tools and workflows companies should automate first • How AI is transforming hiring and recruitment processes If you're building products, leading a startup, or exploring how AI can reshape your internal operations, this episode provides practical insights into the next generation of AI-native companies. Episode length: ~30 minutes 👤 ABOUT THE GUEST Sean Griffith Founder of Truffle → LinkedIn: https://www.linkedin.com/in/griffithsean/ → Company: https://www.hiretruffle.com/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    31 min
  5. AI Implementation in Sales & Product Teams | Alexis d'Eudeville (Lemlist)

    12 MARS

    AI Implementation in Sales & Product Teams | Alexis d'Eudeville (Lemlist)

    Most companies talk about AI. Very few actually implement it in production. In this episode of Business AI Explained, Vladimir de Ziegler sits down with Alexis d'Eudeville, AI Product Manager at Lemlist, to discuss how AI is being used inside real companies. Alexis shares practical lessons from building AI products, launching startups, and working at Google. They explore how AI is transforming product management, sales automation, and go-to-market strategy and why the most important factor is still keeping humans in the loop. The conversation covers: • How AI is implemented inside modern sales teams • The role of generative AI in product management • Why data quality matters for AI adoption • How companies can move from experimentation to AI in production • Practical examples of AI improving marketing and customer success If you're a founder, operator, or builder trying to understand how AI is actually used inside businesses, this episode breaks down the real strategies behind AI implementation. Key Topics: AI implementation in business AI in product management Sales automation and RevOps Go-to-market strategy AI in production systems Chapters:00:00 Introduction – Alexis d'Eudeville & AI at Lemlist 01:45 AI in Business: Why Implementation Matters 05:12 How Companies Are Using AI in Production 08:30 Generative AI for Content and Data Analysis 12:45 Human-in-the-Loop AI and Ethical Considerations 18:20 The Future of AI Tools in Business Workflows 22:15 Real AI Examples in Marketing and Customer Success 27:40 AI Adoption Challenges for Startups and SMEs 31:05 How Companies Can Successfully Implement AI 35:50 Key Takeaways: AI Impact on Business Growth 38:15 Final Thoughts on the Future of AI Episode length: ~40 minutes 👤 ABOUT THE GUEST Alexis d’Eudeville AI Product Manager at Lemlist → LinkedIn: https://www.linkedin.com/in/alexis-d-eudeville-348bb858/ → Company: https://www.lemlist.com/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    40 min
  6. GTM AI Teams: The 3:1 Dev Ratio (And Why It Works) - David Arnoux

    23 FÉVR.

    GTM AI Teams: The 3:1 Dev Ratio (And Why It Works) - David Arnoux

    GTM AI teams break down the moment you try to scale beyond a few workflows into real operations. David Arnoux is a fractional GTM AI strategist who sits inside companies building AI implementation, not just advising.  He runs Gen AI Circle (400+ heavy AI adopters) and has worked with scale-ups and enterprise companies transforming their go-to-market teams with AI. In this episode of Business AI Explained, we break down how AI-native GTM teams actually work, what the team structure looks like, and why the best ones now run a 3:1 ratio of developers to marketers. We cover: How to audit a company's AI readiness (and the red flags that mean they're not ready)The maturity levels of AI implementation: from basic prompting to autonomous loopsPerformance marketing as a self-learning loop (campaigns that optimize themselves)Why "repo ownership" is now strategic power, the person who controls context controls outcomesThe 3:1 developer-to-marketer ratio in cutting-edge GTM teams (and why AI is literally the third team member)Buy vs. build framework: when to use off-the-shelf tools vs. building customThe two internets theory: one for humans (doom scrolling), one for agents (decision-making)Why SEO is becoming "programmatic listicles" to game LLMsThe revenge of the 1950s: why authenticity, friction, and in-person events matter more than everHow to work remotely while transforming companies (90% remote, 10% in-person)This conversation is for CMOs, CROs, GTM leaders, and operators who need to figure out how AI actually fits into their team structure, not just tools, but people. Episode length: ~45 minutes 👤 ABOUT THE GUEST David Arnoux  Fractional GTM AI Strategist | Founder, Gen AI Circle Works with scale-ups and enterprise companies on AI GTM transformation.  Builds ventures through Humanoids studio (including ViralBrain.ai) → LinkedIn: https://www.linkedin.com/in/davidarnoux  → Company: https://www.heyarnoux.com/ → Community: https://www.thegenaicircle.com/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    39 min
  7. AI in Operations for Hardware Companies - Eliott Wertheimer, VanMoof CEO

    23 FÉVR.

    AI in Operations for Hardware Companies - Eliott Wertheimer, VanMoof CEO

    AI in operations for hardware companies looks very different from AI in software, especially after a bankruptcy. Eliott Wertheimer is the CEO of VanMoof, the iconic European e-bike brand rebuilding after bankruptcy. In this episode of Business AI Explained, we explore AI in operations for hardware companies and what it takes to rebuild trust, reliability, and economics in a physical product business. We cover: Why VanMoof’s brand survived bankruptcyThe economics that killed VanMoof 1.0 (low margins, returns, D2C)Rebuilding trust through over-delivery, not marketing promisesWhere AI actually fits in hardware companies (support, supply chain, maintenance)Why AI should be an operational tool, not a product featureWhy brand and design matter more as hardware gets easier to buildThis episode is for founders, operators, and product leaders working on hardware, consumer brands, or complex operations and trying to apply AI without breaking trust. Episode length: ~40 minutes 👤 ABOUT THE GUEST Eliott Wertheimer CEO of VanMoof Former McLaren (Lavoie), founder of Fuero Systems Aerospace engineer turned hardware operator → LinkedIn: https://www.linkedin.com/in/eliott-wertheimer-6910a1b6/ → Company: https://www.vanmoof.com/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    43 min
  8. AI Implementation in Go-To-Market (GTM) - Abraham Gomez, Google

    18 FÉVR.

    AI Implementation in Go-To-Market (GTM) - Abraham Gomez, Google

    AI implementation in go-to-market (GTM) breaks down the moment it moves from demos into real teams. Abraham Gomez is a Strategic Startups Customer Engineer at Google, where he has advised 400+ founders on AI implementation in go-to-market (GTM) teams.  In this episode of Business AI Explained, we break down how AI actually gets implemented inside sales, marketing, and GTM operations and why most teams struggle once AI moves beyond experimentation. We cover: How to choose your first AI implementation in GTMThe 80/20 rule: which AI workflows actually deliver ROIBuy vs. build decisions for AI tools (including when not to use Google’s)Accuracy vs. precision in AI systems, and why domain expertise matters more than modelsWhy AI adoption fails even when the tech worksHow to plan AI projects knowing models change every 6–12 monthsThis conversation is for founders, COOs, RevOps leaders, and operators who need AI to work inside real GTM teams, not just look good in demos. Episode length: ~50 minutes 👤 ABOUT THE GUEST Abraham Gomez Strategic Startups Customer Engineer at Google Works with startups implementing AI in GTM, operations, and core workflows. → LinkedIn: https://www.linkedin.com/in/goabego/ → WhoInvitedAbe Podcast: https://www.youtube.com/@WhoInvitedAbe → Website: https://goabego.com/ 🔗 WORK WITH VLAD If you’re implementing AI in your operations and want hands-on help building real workflows: 👉 https://www.elementsagents.com/ 🔔 SUBSCRIBE → Linkedin: https://www.linkedin.com/in/vladeziegler/ → AI with Vlad: https://www.youtube.com/@aiwithvlad Watch the full video version on YouTube: https://www.youtube.com/@aiwithvlad New episodes every Tuesday.

    57 min

À propos

Business AI Explained is a podcast for founders and go-to-market teams who want to understand how AI creates real business impact. Hosted by Vlad de Ziegler, the show features conversations with builders, operators, and revenue leaders implementing AI in sales, marketing, RevOps, and customer success. Expect real examples, real constraints, and clear lessons from AI in production, not theory.

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